.. summary-start
 

 |logo| adaptive
 ===============

 |PyPI| |Conda| |Downloads| |Pipeline status| |DOI| |Binder| |Gitter|

 |Documentation| |Coverage| |GitHub|

   *Adaptive*: parallel active learning of mathematical functions.

 ``adaptive`` is an open-source Python library designed to

 make adaptive parallel function evaluation simple. With ``adaptive`` you
 just supply a function with its bounds, and it will be evaluated at the
 “best” points in parameter space. With just a few lines of code you can
 evaluate functions on a computing cluster, live-plot the data as it
 returns, and fine-tune the adaptive sampling algorithm.
 

 Run the ``adaptive`` example notebook `live on

 Binder <https://mybinder.org/v2/gh/python-adaptive/adaptive/master?filepath=example-notebook.ipynb>`_

 to see examples of how to use ``adaptive`` or visit the
 `tutorial on Read the Docs <https://adaptive.readthedocs.io/en/latest/tutorial/tutorial.html>`__.

 
 .. summary-end
 
 **WARNING: adaptive is still in a beta development stage**
 

 .. not-in-documentation-start

 
 Implemented algorithms
 ----------------------
 
 The core concept in ``adaptive`` is that of a *learner*. A *learner*
 samples a function at the best places in its parameter space to get
 maximum “information” about the function. As it evaluates the function
 at more and more points in the parameter space, it gets a better idea of
 where the best places are to sample next.
 
 Of course, what qualifies as the “best places” will depend on your
 application domain! ``adaptive`` makes some reasonable default choices,
 but the details of the adaptive sampling are completely customizable.
 
 The following learners are implemented:
 
 - ``Learner1D``, for 1D functions ``f: ℝ → ℝ^N``,
 - ``Learner2D``, for 2D functions ``f: ℝ^2 → ℝ^N``,
 - ``LearnerND``, for ND functions ``f: ℝ^N → ℝ^M``,
 - ``AverageLearner``, For stochastic functions where you want to
   average the result over many evaluations,
 - ``IntegratorLearner``, for
   when you want to intergrate a 1D function ``f: ℝ → ℝ``,
 - ``BalancingLearner``, for when you want to run several learners at once,
   selecting the “best” one each time you get more points.
 
 In addition to the learners, ``adaptive`` also provides primitives for
 running the sampling across several cores and even several machines,
 with built-in support for
 `concurrent.futures <https://docs.python.org/3/library/concurrent.futures.html>`_,
 `ipyparallel <https://ipyparallel.readthedocs.io/en/latest/>`_ and
 `distributed <https://distributed.readthedocs.io/en/latest/>`_.
 
 Examples
 --------
 
 .. raw:: html
 

   <img src="https://user-images.githubusercontent.com/6897215/38739170-6ac7c014-3f34-11e8-9e8f-93b3a3a3d61b.gif" width='20%'> </img> <img src="https://user-images.githubusercontent.com/6897215/35219611-ac8b2122-ff73-11e7-9332-adffab64a8ce.gif" width='40%'> </img> <img src="https://user-images.githubusercontent.com/6897215/47256441-d6d53700-d480-11e8-8224-d1cc49dbdcf5.gif" width='20%'> </img>

 .. not-in-documentation-end

 
 Installation
 ------------
 
 ``adaptive`` works with Python 3.6 and higher on Linux, Windows, or Mac,
 and provides optional extensions for working with the Jupyter/IPython
 Notebook.
 
 The recommended way to install adaptive is using ``conda``:
 
 .. code:: bash
 
     conda install -c conda-forge adaptive
 
 ``adaptive`` is also available on PyPI:
 
 .. code:: bash
 
     pip install adaptive[notebook]
 
 The ``[notebook]`` above will also install the optional dependencies for
 running ``adaptive`` inside a Jupyter notebook.
 
 Development
 -----------
 
 Clone the repository and run ``setup.py develop`` to add a link to the
 cloned repo into your Python path:
 
 .. code:: bash
 
     git clone git@github.com:python-adaptive/adaptive.git
     cd adaptive
     python3 setup.py develop
 
 We highly recommend using a Conda environment or a virtualenv to manage
 the versions of your installed packages while working on ``adaptive``.
 
 In order to not pollute the history with the output of the notebooks,
 please setup the git filter by executing
 
 .. code:: bash
 
     python ipynb_filter.py
 
 in the repository.
 

 We implement several other checks in order to maintain a consistent code style. We do this using `pre-commit <https://pre-commit.com>`_, execute

 
 .. code:: bash
 
     pre-commit install
 
 in the repository.
 

 Citing
 ------
 
 If you used Adaptive in a scientific work, please cite it as follows.
 

 .. code:: bib

 
     @misc{Nijholt2019,
       doi = {10.5281/zenodo.1182437},
       author = {Bas Nijholt and Joseph Weston and Jorn Hoofwijk and Anton Akhmerov},
       title = {\textit{Adaptive}: parallel active learning of mathematical functions},
       publisher = {Zenodo},
       year = {2019}
     }
 

 Credits
 -------
 
 We would like to give credits to the following people:
 
 - Pedro Gonnet for his implementation of `CQUAD <https://www.gnu.org/software/gsl/manual/html_node/CQUAD-doubly_002dadaptive-integration.html>`_,
   “Algorithm 4” as described in “Increasing the Reliability of Adaptive
   Quadrature Using Explicit Interpolants”, P. Gonnet, ACM Transactions on
   Mathematical Software, 37 (3), art. no. 26, 2010.
 - Pauli Virtanen for his ``AdaptiveTriSampling`` script (no longer
   available online since SciPy Central went down) which served as

   inspiration for the `~adaptive.Learner2D`.
 
 .. credits-end

 
 For general discussion, we have a `Gitter chat
 channel <https://gitter.im/python-adaptive/adaptive>`_. If you find any

 bugs or have any feature suggestions please file a GitHub
 `issue <https://github.com/python-adaptive/adaptive/issues/new>`_
 or submit a `pull
 request <https://github.com/python-adaptive/adaptive/pulls>`_.

 
 .. references-start

 .. |logo| image:: https://adaptive.readthedocs.io/en/latest/_static/logo.png

 .. |PyPI| image:: https://img.shields.io/pypi/v/adaptive.svg
    :target: https://pypi.python.org/pypi/adaptive

 .. |Conda| image:: https://img.shields.io/badge/install%20with-conda-green.svg

    :target: https://anaconda.org/conda-forge/adaptive

 .. |Downloads| image:: https://img.shields.io/conda/dn/conda-forge/adaptive.svg

    :target: https://anaconda.org/conda-forge/adaptive

 .. |Pipeline status| image:: https://dev.azure.com/python-adaptive/adaptive/_apis/build/status/python-adaptive.adaptive?branchName=master
    :target: https://dev.azure.com/python-adaptive/adaptive/_build/latest?definitionId=6?branchName=master

 .. |DOI| image:: https://img.shields.io/badge/doi-10.5281%2Fzenodo.1182437-blue.svg
    :target: https://doi.org/10.5281/zenodo.1182437

 .. |Binder| image:: https://mybinder.org/badge.svg

    :target: https://mybinder.org/v2/gh/python-adaptive/adaptive/master?filepath=example-notebook.ipynb

 .. |Gitter| image:: https://img.shields.io/gitter/room/nwjs/nw.js.svg

    :target: https://gitter.im/python-adaptive/adaptive

 .. |Documentation| image:: https://readthedocs.org/projects/adaptive/badge/?version=latest

    :target: https://adaptive.readthedocs.io/en/latest/?badge=latest

 .. |GitHub| image:: https://img.shields.io/github/stars/python-adaptive/adaptive.svg?style=social
    :target: https://github.com/python-adaptive/adaptive/stargazers

 .. |Coverage| image:: https://img.shields.io/codecov/c/github/python-adaptive/adaptive
    :target: https://codecov.io/gh/python-adaptive/adaptive

 .. references-end